Climate model projections suggest major North American biome shifts in response to anthropogenic climate change (Rehfeldt et al. 2012). Such shifts could have profound influences on native flora and fauna, many of which would have to move long distances to track their climatic niches. To evaluate potential ecosystem changes at a somewhat finer scale, I projected the change in climate space for level III ecoregions (Commission for Environmental Cooperation 1997) as surrogates for multiple associated species and ecological communities. First, I developed a random forest model (Breiman 2001) to predict ecoregion class from bioclimatic variables, using 1-km interpolated climate data for the 1969-1990 normal period (Wang et al. 2016),available at adaptwest.databasin.org.

R Code for this portion follows:

library(randomForest)
library(raster)

#eco = project directory
setwd(eco)
datlcc = read.csv("CECEcoregionSampleLCC.csv")
cececo = read.csv("CECecoregions.csv")
ecolevel3s <- read.csv("NA_CEC_Eco_Level3_LCC.shp")
#ecolevel3r = ecoregion raster with a Lambert azimuthal equal-area projection ("ceclev3idlaz.tif")
#lazea <-  CRS("+proj=laea +lat_0=45 +lon_0=-100 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0")
LCC <- CRS("+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs")

#coordinates(datlaz) <- c("X", "Y") 
#proj4string(datlaz) <- CRS("+proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0")

#cur = directory containing grids representing derived climate variables
setwd(cur)
clim <- list.files(cur, pattern =".asc$")
curclim<-stack(clim)
temp <- raster(clim[1])
ID <- as.data.frame(rasterToPoints(temp))
names(ID)[3] <- "ID4km"
ID$ID <- row.names(ID)
IDR <- raster(ncols=ncol(temp), nrows=nrow(temp), xmn=xmin(temp), xmx=xmax(temp), ymn=ymin(temp), ymx=ymax(temp))
IDRR <- rasterize(as.matrix(ID[,1:2]), IDR, as.numeric(ID[,4]))
curclim <- addLayer(curclim,IDRR)

setwd(eco)
sampleclim<-cbind(datlcc,extract(curclim,as.matrix(cbind(datlcc[,3],datlcc[,4]))))
sc <- na.omit(sampleclim)
names(sc)[ncol(sc)] <- "IDgrid"
sc$NA_L3CODE <- as.factor(as.character(sc$NA_L3CODE))
lu <- as.data.frame(levels(sc$NA_L3CODE))
lu$level <- row.names(lu)
names(lu)[1] <- "NA_L3CODE"
write.csv(lu,file="ecoregionlu.csv",row.names=FALSE)

eco.rf <- randomForest(y=sc$NA_L3CODE, x=sc[,5:(ncol(sc)-1)],importance = TRUE, proximity = TRUE, data=sc)
#eco1.rf <- randomForest(y=sc$NA_L3CODE, x=sc[,5:23],importance = TRUE, proximity = TRUE, data=sc)
round(importance(eco.rf), 2)
varImpPlot(eco.rf) 
ecocurr <- predict(curclim,eco.rf)
projection(ecocurr) <- LCC
#ecocurrlaz <- round(projectRaster(ecocurr, ecolevel3r, method='ngb'),0)
writeRaster(ecocurr,filename="currentlcc.tif",datatype='INT4S',format="GTiff",overwrite=TRUE)
curfreq <- freq(ecocurr)
ecolu <- merge(lu,curfreq,by.x="level",by.y="value")
names(ecolu)[3] <- "curr"

This model was then used to project ecoregions onto future mid-century (2041-2070) and end-of-century (2071-2100) climate conditions. Climate projections were based on 1-km downscaled climate anomalies (Wang et al. 2016) generated by an ensemble of 15 widely-used GCMs from the Coupled Model Intercomparison Project, Phase 5 (CMIP5, Taylor et al. 2012), available at adaptwest.databasin.org. I used representative concentration pathway (RCP) 8.5, to represent the 21st century conditions that are to be expected without dramatic reductions in greenhouse gas emissions or technological fixes (Fuss et al. 2014). I also evaluated RCP 4.5 to represent a future in which significant emissions reductions are achieved.

The following code generates projections for each representative and time period:

fut = directory containing grids representing derived future climate variables
rcp <- c("rcp45","rcp85")
time <- c("2050s","2080s")
for (j in rcp) {
    for (k in time) {
            w  <- paste(fut,"NA_ENSEMBLE_",j,"_",k,"_Bioclim_ASCII/",sep="")
            setwd(w)
            futclim <- list.files(w,pattern=".asc$")
            s <-stack(futclim)
            p <- predict(s,eco.rf)
            projection(p) <- LCC
            futfreq <- as.data.frame(freq(p))
        names(futfreq)[2] <- paste(i,j,sep="_")
        ecolu <- merge(ecolu,futfreq,by.x="level",by.y="value")
            writeRaster(p, filename=paste(eco,"pred",j,k,sep="_"),datatype='INT4S',format="GTiff", overwrite=TRUE)
            }
    }

Results for RCP 4.5 and RCP 8.5 are shown in Figures 1 and 2, respectively:

Figure 1. Model-predicted (a) baseline, (b) mid-century, and (c) end-of-century changes in North American ecoregions for RCP 4.5. Boreal, hemi-boreal, and western forested regions are shown in green and blue-green shades; arctic ecoregions are in blue shades; prairie/parkland ecoregions are in brown shades; and temperate forest ecoregions are in yellow and orange shades (see Table 1 for full list of ecoregions). Boreal ecoregions are also outlined in black.

Figure 1. Model-predicted (a) baseline, (b) mid-century, and (c) end-of-century changes in North American ecoregions for RCP 4.5. Boreal, hemi-boreal, and western forested regions are shown in green and blue-green shades; arctic ecoregions are in blue shades; prairie/parkland ecoregions are in brown shades; and temperate forest ecoregions are in yellow and orange shades (see Table 1 for full list of ecoregions). Boreal ecoregions are also outlined in black.

Figure 2. Model-predicted (a) baseline, (b) mid-century, and (c) end-of-century changes in North American ecoregions for RCP 8.5. Boreal, hemi-boreal, and western forested regions are shown in green and blue-green shades; arctic ecoregions are in blue shades; prairie/parkland ecoregions are in brown shades; and temperate forest ecoregions are in yellow and orange shades (see Table 1 for full list of ecoregions). Boreal ecoregions are also outlined in black.

Figure 2. Model-predicted (a) baseline, (b) mid-century, and (c) end-of-century changes in North American ecoregions for RCP 8.5. Boreal, hemi-boreal, and western forested regions are shown in green and blue-green shades; arctic ecoregions are in blue shades; prairie/parkland ecoregions are in brown shades; and temperate forest ecoregions are in yellow and orange shades (see Table 1 for full list of ecoregions). Boreal ecoregions are also outlined in black.

Next, I used the following code to calculate the change in area (16 km2 pixels) for each Level III ecoregion (Table 1):

groups <- c("rcp45_2050s","rcp45_2080s","rcp85_2050s","rcp85_2080s")
setwd(eco)
for (i in groups) {
    g <- list.files(eco,pattern=i)
    g1 <- grep(pattern=".tif$",g,value=TRUE)
    m <- raster(g1)
    futfreq <- as.data.frame(freq(m))
    names(futfreq)[2] <- i
    ecolu <- merge(ecolu,futfreq,by.x="level",by.y="value")
    }
ecolu1 <- merge(unique(cececo[,c(2:4)]),ecolu[,2:7],by="NA_L3CODE")
write.csv(ecolu1,file="ecoregion_changesummary.csv",row.names=FALSE)

Table 1. Model-projected changes by ecoregion:

NA_L3CODE NA_L3NAME curr rcp45_2041.2070 rcp45_2071.2100 rcp85_2041.2070 rcp85_2071.2100
1.1.2 Baffin and Torngat Mountains 5785 5197 2250 1965 393
10.1.1 Thompson-Okanogan Plateau 3839 5693 3589 3376 2862
10.1.2 Columbia Plateau 5036 5531 4827 5101 5167
10.1.3 Northern Basin and Range 9141 1445 334 647 11
10.1.4 Wyoming Basin 8515 1245 560 448 363
10.1.5 Central Basin and Range 16892 15798 14737 13595 5904
10.1.6 Colorado Plateaus 8002 14825 14476 14470 15813
10.1.7 Arizona/New Mexico Plateau 8877 12827 11906 10181 5301
10.1.8 Snake River Plain 4042 5396 6074 5801 1949
10.2.1 Mojave Basin and Range 7766 10443 13446 16203 32738
10.2.2 Sonoran Desert 7208 13908 16462 17540 27624
10.2.4 Chihuahuan Desert 10202 15753 14807 14405 12389
11.1.1 California Coastal Sage, Chaparral, and Oak Woodlands 5946 8910 10364 10810 19407
11.1.2 Central California Valley 3208 2566 2364 2829 1070
11.1.3 Southern and Baja California Pine-Oak Mountains 1794 1249 1059 998 1014
12.1.1 Madrean Archipelago 3214 4902 4809 5281 6232
13.1.1 Arizona/New Mexico Mountains 7069 5884 6871 6695 7784
15.4.1 Southern Florida Coastal Plain 2542 4479 5451 5394 7981
2.1.4 Lancaster and Borden Peninsula Plateaus 5018 321 118 152 9
2.1.5 Foxe Uplands 25575 4649 4173 3141 1985
2.1.6 Baffin Uplands 7702 1641 919 1122 984
2.1.7 Gulf of Boothia and Foxe Basin Plains 11438 400 128 51 75
2.1.9 Banks Island and Amundsen Gulf Lowlands 11202 16289 9323 8539 68
2.2.1 Arctic Coastal Plain 4145 12223 13419 13942 2073
2.2.2 Arctic Foothills 8286 37118 49520 57446 46094
2.2.3 Subarctic Coastal Plains 6951 38956 51348 55642 96698
2.2.4 Seward Peninsula 3685 14046 12792 12515 4386
2.2.5 Bristol Bay-Nushagak Lowlands 4289 15780 18318 17968 23889
2.3.1 Brooks Range/Richardson Mountains 9438 4093 2236 2351 1008
2.4.1 Amundsen Plains 19528 26123 12571 5358 3879
2.4.2 Aberdeen Plains 20284 7377 6876 5852 175
2.4.3 Central Ungava Peninsula and Ottawa and Belcher Islands 12708 989 2019 2766 2328
3.1.1 Interior Forested Lowlands and Uplands 12314 11610 12324 7956 1647
3.1.2 Interior Bottomlands 8480 12243 12947 11485 3740
3.3.2 Hay and Slave River Lowlands 18066 16530 18785 16477 2894
3.4.2 La Grande Hills and New Quebec Central Plateau 23362 2721 289 7 687
3.4.3 Smallwood Uplands 17695 3650 1900 1628 59
3.4.5 Coppermine River and Tazin Lake Uplands 17076 31218 27986 32173 1788
4.1.1 Coastal Hudson Bay Lowland 5247 6216 9476 4593 213
4.1.2 Hudson Bay and James Bay Lowlands 19015 7396 1772 3408 5321
5.1.1 Athabasca Plain and Churchill River Upland 17427 8784 9403 7999 5953
5.1.2 Lake Nipigon and Lac Seul Upland 14113 7979 10656 10468 5219
5.1.3 Central Laurentians and Mecatina Plateau 22320 22361 19161 19597 825
5.1.4 Newfoundland Island 9737 7967 7865 7326 3273
5.1.5 Hayes River Upland and Big Trout Lake 16227 10627 11089 13205 1022
5.1.6 Abitibi Plains and Riviere Rupert Plateau 18020 9554 5260 5975 1
5.2.1 Northern Lakes and Forests 19174 34982 36572 39567 42851
5.2.2 Northern Minnesota Wetlands 2774 36 176 17 2
5.2.3 Algonquin/Southern Laurentians 19758 19809 13374 14844 4684
5.3.1 Northern Appalachian and Atlantic Maritime Highlands 13784 22199 21696 21793 14885
5.4.1 Mid-Boreal Uplands and Peace-Wabaska Lowlands 26281 13199 7792 9977 2322
5.4.2 Clear Hills and Western Alberta Upland 8944 987 610 824 114
5.4.3 Mid-Boreal Lowland and Interlake Plain 8591 21433 22801 23930 17692
6.1.1 Interior Highlands and Klondike Plateau 9208 3124 2530 1914 106
6.1.2 Alaska Range 6968 3714 2627 2487 971
6.1.4 Wrangell and St. Elias Mountains 2554 1378 1049 831 10
6.1.5 Watson Highlands 13655 10757 7553 6807 162
6.1.6 Yukon-Stikine Highlands/Boreal Mountains and Plateaus 10586 5786 3741 3753 353
6.2.1 Skeena-Omineca-Central Canadian Rocky Mountains 9171 8552 8820 9990 2291
6.2.10 Middle Rockies 10794 6030 3226 2347 410
6.2.11 Klamath Mountains 3253 3694 3332 3254 2232
6.2.12 Sierra Nevada 3604 3118 3606 3832 2868
6.2.13 Wasatch and Uinta Mountains 4243 813 238 623 63
6.2.14 Southern Rockies 9092 7227 6959 6111 3052
6.2.15 Idaho Batholith 3999 3728 3623 3928 2089
6.2.2 Chilcotin Ranges and Fraser Plateau 6500 1795 1049 1413 84
6.2.3 Columbia Mountains/Northern Rockies 11119 22325 24278 24061 22864
6.2.4 Canadian Rockies 6511 1408 919 661 61
6.2.5 North Cascades 2717 3194 3353 2192 1064
6.2.6 Cypress Upland 837 556 282 395 885
6.2.7 Cascades 2859 2817 3091 3011 3540
6.2.8 Eastern Cascades Slopes and Foothills 3449 1616 861 741 200
6.2.9 Blue Mountains 4304 6120 6600 6467 3588
7.1.1 Ahklun and Kilbuck Mountains 3741 5592 9927 8813 9255
7.1.2 Alaska Peninsula Mountains 4630 2073 1724 1409 1309
7.1.3 Cook Inlet 2343 7889 6718 5350 2189
7.1.4 Pacific Coastal Mountains 8158 5032 3887 3482 1811
7.1.5 Coastal Western Hemlock-Sitka Spruce Forests 10176 13692 12519 12684 4999
7.1.6 Pacific and Nass Ranges 7173 8014 7731 9747 3648
7.1.7 Strait of Georgia/Puget Lowland 3380 3809 4980 5047 12675
7.1.8 Coast Range 3878 3847 3489 3851 3272
7.1.9 Willamette Valley 1129 2525 3088 2721 3538
8.1.1 Eastern Great Lakes Lowlands 10611 27854 39218 39742 58844
8.1.10 Erie Drift Plain 2274 307 62 6 54
8.1.2 Lake Erie Lowland 4095 890 1202 1076 937
8.1.3 Northern Allegheny Plateau 3060 36 2 4 130
8.1.4 North Central Hardwood Forests 6153 7501 12214 11052 6399
8.1.6 Southern Michigan/Northern Indiana Drift Plains 4974 1858 404 229 281
8.1.7 Northeastern Coastal Zone 3483 16109 16031 17106 9656
8.1.8 Acadian Plains and Hills 6882 1089 364 793 797
8.1.9 Maritime Lowlands 3379 564 4 15 706
8.2.1 Southeastern Wisconsin Till Plains 2639 1175 973 1252 6440
8.2.2 Huron/Erie Lake Plains 3393 4880 5070 3660 4186
8.2.3 Central Corn Belt Plains 5253 1871 1709 2247 4536
8.2.4 Eastern Corn Belt Plains 5195 8044 6701 5080 614
8.3.1 Northern Piedmont 2266 2042 2428 875 220
8.3.2 Interior River Valleys and Hills 7204 18471 22834 32181 41053
8.3.3 Interior Plateau 7863 4882 4497 3481 1847
8.3.4 Piedmont 10363 2622 1337 895 173
8.3.5 Southeastern Plains 15521 9623 12471 8427 3111
8.3.6 Mississippi Valley Loess Plains 4937 811 522 1506 1092
8.3.7 South Central Plains 9328 20114 18219 24925 36606
8.3.8 East Central Texas Plains 3242 8719 9141 10183 11699
8.4.1 Ridge and Valley 5920 904 578 203 422
8.4.2 Central Appalachians 4867 832 448 138 119
8.4.3 Western Allegheny Plateau 4778 947 617 703 13
8.4.4 Blue Ridge 3021 1863 2013 2268 7292
8.4.5 Ozark Highlands 6249 8596 4947 5703 5052
8.4.6 Boston Mountains 1336 310 668 292 230
8.4.7 Arkansas Valley 1969 3349 3055 2012 659
8.4.8 Ouachita Mountains 1619 2407 1589 1016 710
8.4.9 Southwestern Appalachians 3253 312 274 230 523
8.5.1 Middle Atlantic Coastal Plain 7953 4024 7165 1763 5204
8.5.2 Mississippi Alluvial Plain 8327 28746 33976 31813 33331
8.5.3 Southern Coastal Plain 10023 14455 12420 11986 12766
8.5.4 Atlantic Coastal Pine Barrens 1540 6493 9429 7146 10878
9.2.1 Aspen Parkland/Northern Glaciated Plains 19219 43285 40756 47938 53002
9.2.2 Lake Manitoba and Lake Agassiz Plain 7004 31809 43943 43028 71014
9.2.3 Western Corn Belt Plains 13086 15829 14529 15256 36825
9.2.4 Central Irregular Plains 7590 12209 7936 12002 2564
9.3.1 Northwestern Glaciated Plains 22953 15444 13530 12853 23046
9.3.3 Northwestern Great Plains 22220 26844 24463 22722 4034
9.3.4 Nebraska Sand Hills 5161 281 272 251 40
9.4.1 High Plains 17009 25323 27925 26333 13500
9.4.2 Central Great Plains 14563 39122 52642 46814 122654
9.4.3 Southwestern Tablelands 12148 19747 18592 20378 21736
9.4.4 Flint Hills 2576 46 33 5 79
9.4.5 Cross Timbers 5772 10147 11004 10631 26257
9.4.6 Edwards Plateau 5712 155 44 39 14
9.4.7 Texas Blackland Prairies 3141 1303 1032 1451 4601
9.5.1 Western Gulf Coastal Plain 5505 14913 20089 20010 39523
9.6.1 Southern Texas Plains/Interior Plains and Hills with Xerophytic Shrub and Oak Forest 2942 13180 15724 17877 25204

I also specifically summarized changes for boreal ecoregions (4.1, 5.4, 5.1, 3.4, 3.3, 3.2, 3.1, and 6.1) (Table 2):

Table 2. Model-projected changes by boreal ecoregion:

NA_L3CODE NA_L3NAME curr rcp45_2041.2070 rcp45_2071.2100 rcp85_2041.2070 rcp85_2071.2100
3.1.1 Interior Forested Lowlands and Uplands 12314 11610 12324 7956 1647
3.1.2 Interior Bottomlands 8480 12243 12947 11485 3740
3.3.2 Hay and Slave River Lowlands 18066 16530 18785 16477 2894
3.4.2 La Grande Hills and New Quebec Central Plateau 23362 2721 289 7 687
3.4.3 Smallwood Uplands 17695 3650 1900 1628 59
3.4.5 Coppermine River and Tazin Lake Uplands 17076 31218 27986 32173 1788
4.1.1 Coastal Hudson Bay Lowland 5247 6216 9476 4593 213
4.1.2 Hudson Bay and James Bay Lowlands 19015 7396 1772 3408 5321
5.1.1 Athabasca Plain and Churchill River Upland 17427 8784 9403 7999 5953
5.1.2 Lake Nipigon and Lac Seul Upland 14113 7979 10656 10468 5219
5.1.3 Central Laurentians and Mecatina Plateau 22320 22361 19161 19597 825
5.1.4 Newfoundland Island 9737 7967 7865 7326 3273
5.1.5 Hayes River Upland and Big Trout Lake 16227 10627 11089 13205 1022
5.1.6 Abitibi Plains and Riviere Rupert Plateau 18020 9554 5260 5975 1
5.4.1 Mid-Boreal Uplands and Peace-Wabaska Lowlands 26281 13199 7792 9977 2322
5.4.2 Clear Hills and Western Alberta Upland 8944 987 610 824 114
5.4.3 Mid-Boreal Lowland and Interlake Plain 8591 21433 22801 23930 17692
6.1.1 Interior Highlands and Klondike Plateau 9208 3124 2530 1914 106
6.1.2 Alaska Range 6968 3714 2627 2487 971
6.1.4 Wrangell and St. Elias Mountains 2554 1378 1049 831 10
6.1.5 Watson Highlands 13655 10757 7553 6807 162
6.1.6 Yukon-Stikine Highlands/Boreal Mountains and Plateaus 10586 5786 3741 3753 353

This translates into 14% and 42% losses of boreal climate space by 2041-2070 and 2071-2100, respectively, based on RCP 8.5; or 9% and 13% losses based on RCP 4.5

Change projections can be found at adaptwest.databasin.org.

References

Breiman, L. 2001. Random Forests. Machine Learning 45:5-32.

Commission for Environmental Cooperation. 1997. Ecological Regions of North America: Toward a Common Perspective, Montreal, Canada.

Fuss, S., J. G. Canadell, G. P. Peters, M. Tavoni, R. M. Andrew, P. Ciais, R. B. Jackson, C. D. Jones, F. Kraxner, N. Nakicenovic, C. Le Quere, M. R. Raupach, A. Sharifi, P. Smith, and Y. Yamagata. 2014. Betting on negative emissions. Nature Climate Change 4:850-853.

McKenney, D., J. Pedlar, M. Hutchinson, P. Papadopol, K. Lawrence, K. Campbell, E. Milewska, R. F. Hopkinson, and D. Price. 2013. Spatial climate models for Canada’s forestry community. The Forestry Chronicle 89:659-663.

Rehfeldt, G. E., N. L. Crookston, C. Sáenz-Romero, and E. M. Campbell. 2012. North American vegetation model for land-use planning in a changing climate: a solution to large classification problems. Ecological Applications 22:119-141.

Taylor, K. E., R. J. Stouffer, and G. A. Meehl. 2012. An Overview of CMIP5 and the Experiment Design. Bulletin of the American Meteorological Society 93:485-498.

Wang, T., A. Hamann, D. Spittlehouse, and C. Carroll. 2016. Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America. PLoS ONE 11:e0156720.